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The analysis of growth curves has long been important in biostatistics. Work has focused on two problems: the estimation of individual curves based on many data points, and the estimation of the mean growth curve for a group of individuals. This paper extends a recent approach that seeks to combine data from a group of individuals in order to improve the estimates of individual growth parameters. Growth is modeled as polynomial in time, and the group model is also linear, incorporating growth-related covariates into the model. The estimation used is empirical Bayes. The estimation formulas are illustrated with a set of data on rat growth, originally presented by Box (1950, Biometrics 6, 362-389).
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Judith F. Strenio
Herbert I. Weisberg
Path BioAnalytics (United States)
Anthony S. Bryk
Carnegie Foundation for the Advancement of Teaching
Biometrics
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Strenio et al. (Tue,) studied this question.
synapsesocial.com/papers/6a1928c3a0353395e957f056 — DOI: https://doi.org/10.2307/2530808